电压源谐振变换器广泛应用于介质阻挡放电薄膜表面处理领域,其放电波形是影响薄膜表面处理效果的重要因素。首先分别对连续电流模式和断续电流模式下的电压源谐振变换器进行时域解析,证明了断续电流模式下放电电流波形能独立于功率而自...电压源谐振变换器广泛应用于介质阻挡放电薄膜表面处理领域,其放电波形是影响薄膜表面处理效果的重要因素。首先分别对连续电流模式和断续电流模式下的电压源谐振变换器进行时域解析,证明了断续电流模式下放电电流波形能独立于功率而自由调节,而连续电流模式下放电电流波形与功率耦合而无法独立调节。然后以此为基础,设计并搭建了2台连续电流模式和断续电流模式的350 W/30 k Hz变换器样机,对双轴向聚丙烯、流延聚丙烯和聚酯三种材料样品进行了表面处理和效果对比。结果表明:在相同功率和频率下,与连续电流模式相比,断续电流模式中谐振电感越小,放电脉宽越窄,峰值电流越大,塑料薄膜的表面接触角越小,处理效果越好;断续电流模式下减小谐振电感可缩短放电脉宽,使得达到相同表面处理效果所需功率越小,实现了节能目的。展开更多
A reliable, efficient and economical power supply for dielectric barrier discharge （DBD） is essential for its industrial applications. However, the equivalent load parameters complicare the design of power supply as...A reliable, efficient and economical power supply for dielectric barrier discharge （DBD） is essential for its industrial applications. However, the equivalent load parameters complicare the design of power supply as they are variable and varied nonlinearly in response to varied voltage and power. In this paper the equivalent electrical parameters of DBD are predicted using a neural network, which is beneficial for the design of power supply and helps to investigate how the electrical parameters influence the equivalent load parameters. The electrical parameters includ- ing voltage and power are determined to be the inputs of the neural network model, as these two parameters greatly influence the discharge type and the equivalent DBD load parameters which are the outputs of the model. The voltage and power are decoupled with pulse density modula- tion （PDM） and hence the impact of the two electrical parameters is discussed individually. The neural network model is trained with the back-propagation （BP） algorithm. The obtained neural network model is evaluated by the relative error, and the prediction has a good agreement with the practical values obtained in experiments.展开更多
The structures of Y2Fe17-xCrx are simulated by the ab initio potentials. The site preference of Cr atom in Y2Fe17 is evaluated and the order is determined as 4f, 12j, which is close to the experimental result. Based o...The structures of Y2Fe17-xCrx are simulated by the ab initio potentials. The site preference of Cr atom in Y2Fe17 is evaluated and the order is determined as 4f, 12j, which is close to the experimental result. Based on the site preference behavior, the calculated parameters and the atom sites of Y-Fe-Cr system are studied. The result corresponds well to observed data. Further, the DOS of the relaxed structures are calculated and the variation in Curie temperature is explained qualitatively by the spin-fluctuation theory.展开更多
文摘电压源谐振变换器广泛应用于介质阻挡放电薄膜表面处理领域,其放电波形是影响薄膜表面处理效果的重要因素。首先分别对连续电流模式和断续电流模式下的电压源谐振变换器进行时域解析,证明了断续电流模式下放电电流波形能独立于功率而自由调节,而连续电流模式下放电电流波形与功率耦合而无法独立调节。然后以此为基础,设计并搭建了2台连续电流模式和断续电流模式的350 W/30 k Hz变换器样机,对双轴向聚丙烯、流延聚丙烯和聚酯三种材料样品进行了表面处理和效果对比。结果表明:在相同功率和频率下,与连续电流模式相比,断续电流模式中谐振电感越小,放电脉宽越窄,峰值电流越大,塑料薄膜的表面接触角越小,处理效果越好;断续电流模式下减小谐振电感可缩短放电脉宽,使得达到相同表面处理效果所需功率越小,实现了节能目的。
基金supported by National Natural Science Foundation of China(Nos.51107115,11347125,51407156)China Postdoctoral Science Foundation(Nos.20110491766,2014M551735)
文摘A reliable, efficient and economical power supply for dielectric barrier discharge （DBD） is essential for its industrial applications. However, the equivalent load parameters complicare the design of power supply as they are variable and varied nonlinearly in response to varied voltage and power. In this paper the equivalent electrical parameters of DBD are predicted using a neural network, which is beneficial for the design of power supply and helps to investigate how the electrical parameters influence the equivalent load parameters. The electrical parameters includ- ing voltage and power are determined to be the inputs of the neural network model, as these two parameters greatly influence the discharge type and the equivalent DBD load parameters which are the outputs of the model. The voltage and power are decoupled with pulse density modula- tion （PDM） and hence the impact of the two electrical parameters is discussed individually. The neural network model is trained with the back-propagation （BP） algorithm. The obtained neural network model is evaluated by the relative error, and the prediction has a good agreement with the practical values obtained in experiments.
基金Special Funds for Major State Basic Research of China(Grant Nos.G2000067101,and G2000067106)the National Natural Science Foundation of China(Grant No.59971006)
文摘The structures of Y2Fe17-xCrx are simulated by the ab initio potentials. The site preference of Cr atom in Y2Fe17 is evaluated and the order is determined as 4f, 12j, which is close to the experimental result. Based on the site preference behavior, the calculated parameters and the atom sites of Y-Fe-Cr system are studied. The result corresponds well to observed data. Further, the DOS of the relaxed structures are calculated and the variation in Curie temperature is explained qualitatively by the spin-fluctuation theory.
